Canine Adenovirus 2: A Natural Choice for Brain Circuit Dissection
Bibliographic record
Abstract
Canine adenovirus-2 (CAV) is a canine pathogen that has been used in a variety of applications, from vaccines against more infectious strains of CAV to treatments for neurological disorders. With recent engineering, CAV has become a natural choice for neuroscientists dissecting the connectivity and function of brain circuits. Specifically, as a reliable genetic vector with minimal immunogenic and cytotoxic reactivity, CAV has been used for the retrograde transduction of various types of projection neurons. Consequently, CAV is particularly useful when studying the anatomy and functions of long-range projections. Moreover, combining CAV with conditional expression and transsynaptic tracing results in the ability to study circuits with cell- and/or projection-type specificity. Lastly, with the well-documented knowledge of viral transduction, new innovations have been developed to increase the transduction efficiency of CAV and circumvent its tropism, expanding the potential of CAV for circuit analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".